Detection of Subclinical Pulmonary Edema After Acute ST-segment Elevation Myocardial Infarction Without Heart Failure by Chest Computed Tomography

ABSTRACT BACKGROUND Pulmonary edema is a severe complication in patients with acute myocardial infarction which indicates the development of heart failure (HF) and poor prognosis. However, subclinical pulmonary edema after acute ST-segment elevation myocardial infarction (STEMI) without HF has not received enough attention in clinical practice. We aimed to investigate the prognostic value and associated clinical characteristics of subclinical pulmonary edema after acute STEMI without HF detected by chest computed tomography (CT). METHODS A total of 276 patients with acute STEMI without HF who underwent chest CT were included in this study. K-means clustering analysis was performed to classify the patients into different subgroups based on the mean lung density. Clinical characteristics of the different subgroups were compared and used to establish a machine learning model for discriminating between them. Relative risk (RR) for major adverse cardiovascular events (MACEs) during hospitalization was compared between the subgroups. RESULTS The patients were classified into two subgroups. Subgroup 2 showed higher mean lung density than subgroup 1 (median [IQR], −727 [−747, −704] vs. −806 [−826, −785] HU, P < 0.001), with significantly higher levels of cardiac enzymes and numbers of inflammatory cells and significantly worse left ventricular function than subgroup 1. In the model analysis, the most important clinical characteristics were the levels of cardiac enzymes, numbers of inflammatory cells, and left ventricular function. The risk for MACEs was higher in subgroup 2 than in subgroup 1 (RR, 2.12; P = 0.002). CONCLUSIONS Subclinical pulmonary edema after acute STEMI without HF was mainly associated with elevated levels of cardiac enzymes, followed by increased numbers of inflammatory cells and worse left ventricular function. In addition, subclinical pulmonary edema provided crucial prognostic information for patients during hospitalization.